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CNN SLAM implementation of https://arxiv.org/abs/1704.03489

README

Updated: 4th October 2018.

Computer Vision and Intelligence Group, IIT Madras


Blog: iitmcvg.github.io

This repository contains content that we use for CNN SLAM. Original paper


Contributors

  • Varun Sundar
  • Aditya S
  • Aaaryaan

Table of Contents

  1. Download Monodepth Checkpoints
  2. Using Monodepth Infer
  3. Install g2o

Experiments

  1. Heterogenous graphs; convert every CPU op into a compute graph and note performance with placement.
  2. Stereo matching methods and GPU optimisation.
  3. CPU efficient object detectors and depth estimators.
  4. Indoor optimised depth estimation (monocular.)

To Do

  • [x] Complete camera pose estimation.
  • [ ] Monocular depth methods library.
  • [ ] Freeze graphs for inference.
  • [ ] Sample runs.
  • [ ] Global Graph Optimisation.

G3docs

  • Monodepth

Monodepth checkpoints


References

  1. Python Bindings for LSD SLAM
  2. LSD SLAM
  3. Python Bindings for ORB SLAM 2
  4. ORB SLAM
  5. DSO SLAM
  6. A SLAM Primer